Yuri Simione has written a blog post about a content recommendation engine for the Documentum Content Server that he’s been working on. Yuri is looking for Documentum users to beta test the technology so get in touch if that’s you.

In Max De Marzi‘s latest blog post he shows how to write a user defined procedure that combines graph pattern matching and fuzzy text search to find duplicate people in a graph.

APOC adds HDFS support, aggregation functions, and path functions

This week Michaelreleased a new version of the popular APOC library. The library just crossed 500 GitHub stars so thanks to everyone for your support.

This release has lots of new goodies to play with, including support for writing and reading from HDFS, using S3 URIs when loading data, aggregation functions, full document indexing, path expander sequences, and much more.

The library now contains more than 400 procedures and functions so there’s bound to be something in there that’s useful for your project.

Don’t forget to star the project if it’s been helpful so that more people can find it.

Cypher for Gremlin, Neo4j in RMarkdown, Cypher vs SQL aggregations

Colin Fay has started working on rmd4j, which aims to provide a knitr engine for running Neo4J inside RMarkdown. This one is still in its early stages so don’t forget to give Colin some feedback if you try it out.

Conrad Taylor has written up some notes from the NetIKX January meeting. There’s an interesting comparison of Relational and Graph Databases and also a discussion of linked data and the semantic web.

On the podcast: Jonathan Schmidt

This week on the podcast Rik interviewed Jonathan Schmidt, founder and CTO of Waykonect, a startup that offers intelligent vehicle management based on Neo4j.

Jonathan explains how Waykonect use Neo4j to map the relationship between the telematic dongle, the vehicle, the account that manages the vehicle, the driver that drives the vehicle, the trips that are recorded, events that happen on that trip, and the maintenance of the vehicle.

In a very interesting technical discussion they also talk about the rest of Waykonect’s architecture, including Kafka as the messaging back bone and InfluxDB for time series analysis.

Tweet of the Week

I am really liking this stream to gephi procedure in @neo4j. Here is our lesson learned db, green Topic nodes sized by # of pink lessons in the topic. Next to show correlation between topics. I'll stop soon. #rstats#neo4jpic.twitter.com/mEmZSbhrOK

3 Comments

Jonathan’s integration of neo4j with Waykonect sounds super interesting, will definitely be checking out the podcast. It would be great if you could embed SoundCloud podcasts directly into future blog posts 🙂